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Related Experiment Video

Updated: May 8, 2026

Combining Behavioral Endocrinology and Experimental Economics: Testosterone and Social Decision Making
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Published on: March 2, 2011

Social learning in the ultimatum game.

Boyu Zhang1

  • 1School of Mathematical Sciences, Beijing Normal University, Beijing, P.R. China.

Plos One
|September 12, 2013
PubMed
Summary

In the ultimatum game, boundedly rational players exhibit fairness. Social learning leads to oscillations between 40-50% offers, with rare mutations favoring fair behavior.

Area of Science:

  • Behavioral Economics
  • Game Theory
  • Computational Social Science

Background:

  • The ultimatum game involves two players dividing money, with a proposer offering a split and a responder accepting or rejecting.
  • Rational economic theory predicts responders accept any offer, but human behavior shows a preference for fairness.
  • Bounded rationality and estimation errors in strategy payoffs are key factors in observed player behavior.

Purpose of the Study:

  • To investigate the dynamics of the ultimatum game using a learning-mutation process.
  • To model boundedly rational players who make mistakes in estimating strategy payoffs.
  • To analyze how social learning and mutation rates influence the emergence of fairness.

Main Methods:

  • Utilizing a learning-mutation process grounded in quantal response equilibrium.

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  • Simulating player interactions where strategies are learned and subject to random mutations.
  • Analyzing the long-term outcomes of social learning under varying mutation rates (local and global).

    • Main Results:

    • Social learning in the ultimatum game does not stabilize at purely rational or fair outcomes.
    • Observed offer dynamics oscillate between 40% and 50% of the total sum.
    • Offers below 40% tend to increase, while offers reaching fairness (50%) tend to decrease.

    Conclusions:

    • Fairness is favored in the long run when mutation rates are low (local mutation).
    • High mutation rates can promote the evolution of fairness, regardless of mutation scope (local or global).
    • The model demonstrates that fairness can emerge and persist in economic games under specific learning and mutation dynamics.